library(cola)
Data is from https://tcga-data.nci.nih.gov/docs/publications/gbm_exp/.
data = read.table("~/analysis/unifiedScaled.txt", header = TRUE, row.names = 1,
check.names = FALSE)
data = as.matrix(data)
subtype = read.table("~/analysis/TCGA_unified_CORE_ClaNC840.txt",
sep = "\t", header = TRUE, check.names = FALSE, stringsAsFactors = FALSE)
subtype = structure(unlist(subtype[1, -(1:2)]), names = colnames(subtype)[-(1:2)])
data = data[, names(subtype)]
dim(data)
## [1] 11861 173
table(subtype)
## subtype
## Classical Mesenchymal Neural Proneural
## 38 56 26 53
Get all supported top methods and partition methods:
all_top_value_methods()
## [1] "sd" "vc" "MAD" "AAC"
all_partition_methods()
## [1] "hclust" "kmeans" "skmeans" "pam" "mclust" "som"
register_top_value_fun(AAC = function(mat) AAC(t(mat), mc.cores = 4))
Run clustering for all combination of methods in batch:
## res_list = run_all_consensus_partition_methods(data, top_n = c(1000, 2000, 4000), k = 2:6, mc.cores = 4,
## known_anno = data.frame(subtype = subtype),
## known_col = list(subtype = structure(seq_len(4), names = unique(subtype))))
## res_list
get_best_k(res_list)
## best_k cophcor PAC mean_silhouette
## sd:hclust 6 0.9094122 0.24330903 0.4994752
## sd:kmeans 4 0.9867934 0.04820241 0.9137934
## sd:skmeans 3 0.9922243 0.03066354 0.9613865
## sd:pam 2 0.9934359 0.03615153 0.9684454
## sd:mclust 2 0.9771780 0.08593616 0.9226205
## sd:som 5 0.9173885 0.22281407 0.6050151
## vc:hclust 6 0.8645741 0.35070442 0.4826868
## vc:kmeans 2 0.9484612 0.16464367 0.8451851
## vc:skmeans 2 0.9729157 0.08327325 0.9188394
## vc:pam 6 0.9608122 0.10457764 0.7834789
## vc:mclust 2 0.9400835 0.12350497 0.8016653
## vc:som 2 0.8078426 0.30816388 0.6152749
## MAD:hclust 6 0.9158306 0.22948724 0.5299491
## MAD:kmeans 4 0.9938793 0.03058575 0.9494560
## MAD:skmeans 3 0.9897329 0.03178744 0.9545245
## MAD:pam 2 0.9913577 0.04219626 0.9619030
## MAD:mclust 2 0.9671705 0.09492363 0.9030578
## MAD:som 6 0.9328326 0.18225361 0.6132457
## AAC:hclust 2 0.8865921 0.26475628 0.7315061
## AAC:kmeans 2 0.9879978 0.06637911 0.9500758
## AAC:skmeans 2 0.9929374 0.02974800 0.9736079
## AAC:pam 2 0.9782622 0.09175420 0.9051787
## AAC:mclust 4 0.9523783 0.21830801 0.7279697
## AAC:som 2 0.9197901 0.25076993 0.7506715
Collect all plots for a k:
collect_plots(res_list, k = 4, fun = plot_ecdf)
collect_plots(res_list, k = 4, fun = consensus_heatmap)
collect_plots(res_list, k = 4, fun = membership_heatmap)
# collect_plots(res_list, k = 3, fun = get_signatures)
get_stat(res_list, k = 4)
## cophcor PAC mean_silhouette tot_withinss
## sd:skmeans 0.9904512 0.02939927 0.9453256 515908.2
## vc:skmeans 0.9055941 0.21837564 0.6286833 571295.4
## MAD:skmeans 0.9921474 0.03839881 0.9438570 515334.7
## AAC:skmeans 0.9839792 0.05661884 0.8978034 480727.7
## sd:mclust 0.9485036 0.23587514 0.7270282 530099.1
## vc:mclust 0.8710222 0.35022307 0.4938555 578485.6
## MAD:mclust 0.9725038 0.15274525 0.8238450 524515.2
## AAC:mclust 0.9523783 0.21830801 0.7279697 488370.6
## sd:som 0.9113848 0.28755205 0.6595718 518174.7
## vc:som 0.8456411 0.38379417 0.4628444 582100.4
## MAD:som 0.9055094 0.29045254 0.6311532 516131.8
## AAC:som 0.8560991 0.30889917 0.5111046 479176.9
## sd:kmeans 0.9867934 0.04820241 0.9137934 514412.8
## vc:kmeans 0.8745586 0.28340348 0.5185240 574381.6
## MAD:kmeans 0.9938793 0.03058575 0.9494560 513463.6
## AAC:kmeans 0.9860569 0.07229192 0.8856360 472855.8
## sd:pam 0.9585691 0.10005773 0.8200042 530782.7
## vc:pam 0.9526215 0.17625776 0.7600683 582850.5
## MAD:pam 0.9636888 0.09483821 0.8203004 527160.4
## AAC:pam 0.9670917 0.08431730 0.8572551 484527.6
## sd:hclust 0.8965037 0.31667222 0.5929598 520805.0
## vc:hclust 0.8566581 0.37164395 0.5434642 588382.0
## MAD:hclust 0.8908500 0.29405492 0.5777541 522589.3
## AAC:hclust 0.8453134 0.32709684 0.4808156 484521.1
## area_increased
## sd:skmeans 0.1228735
## vc:skmeans 0.1219967
## MAD:skmeans 0.1235529
## AAC:skmeans 0.1459457
## sd:mclust 0.1561688
## vc:mclust 0.3440433
## MAD:mclust 0.1902568
## AAC:mclust 0.1597279
## sd:som 0.2104291
## vc:som 0.2345725
## MAD:som 0.1663282
## AAC:som 0.1398289
## sd:kmeans 0.1342628
## vc:kmeans 0.1177357
## MAD:kmeans 0.1289669
## AAC:kmeans 0.1284463
## sd:pam 0.1501228
## vc:pam 0.1782579
## MAD:pam 0.1423781
## AAC:pam 0.1363856
## sd:hclust 0.1970805
## vc:hclust 0.2091184
## MAD:hclust 0.1726574
## AAC:hclust 0.1498017
collect_classes(res_list, k = 4)
Overlap of top rows in different top methods:
par(mfrow = c(1, 3))
top_rows_overlap(res_list, top_n = 1000)
## Loading required namespace: venneuler
top_rows_overlap(res_list, top_n = 2000)
top_rows_overlap(res_list, top_n = 4000)
Also visualize the correspondance of rankings between different scoreing methods:
top_rows_overlap(res_list, top_n = 1000, type = "correspondance")
Heatmaps for the top rows:
top_rows_heatmap(res_list, top_n = 1000)
Get clustering in a specified combination of top method and partition method:
res = get_single_run(res_list, top_method = "MAD", partition_method = "kmeans")
res
## A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
## top rows (1000, 2000, 4000) are extracted by 'MAD' method.
## subgroups are detected by 'kmeans' method.
## best k for subgroups seems to be 4.
##
## Following methods can be applied to this 'ConsensusPartition' object:
## [1] "collect_classes" "collect_plots"
## [3] "consensus_heatmap" "dimension_reduction"
## [5] "get_best_k" "get_class"
## [7] "get_consensus" "get_membership"
## [9] "get_param" "get_signatures"
## [11] "get_stat" "membership_heatmap"
## [13] "plot_ecdf" "select_partition_number"
## [15] "show" "signature_density"
## [17] "test_to_known_factors"
Collect all plots
collect_plots(res)
## Loading required namespace: genefilter
plots:
select_partition_number(res)
get_best_k(res)
## [1] 4
consensus_heatmap(res, k = 4)
membership_heatmap(res, k = 4)
# get_signatures(res, k = 4)
Get classifications
get_class(res, k = 4)
## class entropy silhouette
## TCGA-02-0003-01A-01 4 0.31715478 0.8054178
## TCGA-02-0010-01A-01 4 0.00000000 0.9881313
## TCGA-02-0011-01B-01 4 0.00000000 0.9881313
## TCGA-02-0014-01A-01 4 0.00000000 0.9881313
## TCGA-02-0024-01B-01 4 0.00000000 0.9881313
## TCGA-02-0026-01B-01 4 0.00000000 0.9881313
## TCGA-02-0028-01A-01 4 0.00000000 0.9881313
## TCGA-02-0046-01A-01 4 0.00000000 0.9881313
## TCGA-02-0047-01A-01 3 0.00000000 0.9674142
## TCGA-02-0048-01A-01 4 0.05107902 0.9753276
## TCGA-02-0060-01A-01 3 0.17667967 0.9214547
## TCGA-02-0069-01A-01 4 0.00000000 0.9881313
## TCGA-02-0074-01A-01 4 0.00000000 0.9881313
## TCGA-02-0080-01A-01 4 0.00000000 0.9881313
## TCGA-02-0084-01A-03 3 0.13603239 0.9296546
## TCGA-02-0087-01A-01 3 0.24488951 0.8818411
## TCGA-02-0104-01A-01 4 0.00000000 0.9881313
## TCGA-02-0114-01A-01 4 0.00000000 0.9881313
## TCGA-02-0281-01A-01 4 0.00000000 0.9881313
## TCGA-02-0321-01A-01 2 0.34722304 0.7797318
## TCGA-02-0325-01A-01 4 0.07072027 0.9689796
## TCGA-02-0338-01A-01 4 0.00000000 0.9881313
## TCGA-02-0339-01A-01 4 0.00000000 0.9881313
## TCGA-02-0432-01A-02 4 0.00000000 0.9881313
## TCGA-02-0439-01A-01 3 0.00000000 0.9674142
## TCGA-02-0440-01A-01 4 0.00000000 0.9881313
## TCGA-02-0446-01A-01 3 0.00000000 0.9674142
## TCGA-06-0128-01A-01 3 0.26468043 0.8672178
## TCGA-06-0129-01A-01 4 0.00000000 0.9881313
## TCGA-06-0146-01A-01 4 0.00000000 0.9881313
## TCGA-06-0156-01A-01 3 0.00000000 0.9674142
## TCGA-06-0166-01A-01 3 0.00000000 0.9674142
## TCGA-06-0174-01A-01 4 0.00000000 0.9881313
## TCGA-06-0177-01A-01 4 0.00000000 0.9881313
## TCGA-06-0238-01A-02 3 0.47659859 0.4194361
## TCGA-06-0241-01A-02 4 0.00000000 0.9881313
## TCGA-06-0410-01A-01 4 0.00000000 0.9881313
## TCGA-06-0413-01A-01 4 0.00000000 0.9881313
## TCGA-06-0414-01A-01 4 0.00000000 0.9881313
## TCGA-06-0646-01A-01 3 0.00000000 0.9674142
## TCGA-06-0648-01A-01 4 0.00000000 0.9881313
## TCGA-08-0245-01A-01 4 0.00000000 0.9881313
## TCGA-08-0344-01A-01 4 0.00000000 0.9881313
## TCGA-08-0347-01A-01 3 0.00000000 0.9674142
## TCGA-08-0348-01A-01 4 0.38607757 0.7005131
## TCGA-08-0350-01A-01 4 0.00000000 0.9881313
## TCGA-08-0353-01A-01 2 0.00000000 0.9574407
## TCGA-08-0359-01A-01 3 0.00000000 0.9674142
## TCGA-08-0385-01A-01 4 0.00000000 0.9881313
## TCGA-08-0517-01A-01 4 0.00000000 0.9881313
## TCGA-08-0524-01A-01 4 0.00000000 0.9881313
## TCGA-12-0616-01A-01 4 0.00000000 0.9881313
## TCGA-12-0618-01A-01 4 0.00000000 0.9881313
## TCGA-02-0089-01A-01 3 0.00000000 0.9674142
## TCGA-02-0113-01A-01 2 0.39752014 0.7128318
## TCGA-02-0115-01A-01 3 0.00000000 0.9674142
## TCGA-02-0451-01A-01 3 0.00000000 0.9674142
## TCGA-06-0132-01A-02 3 0.00000000 0.9674142
## TCGA-06-0133-01A-02 3 0.00000000 0.9674142
## TCGA-06-0138-01A-02 3 0.00000000 0.9674142
## TCGA-06-0160-01A-01 3 0.17667967 0.9214547
## TCGA-06-0162-01A-01 3 0.00000000 0.9674142
## TCGA-06-0167-01A-01 3 0.17667967 0.9214547
## TCGA-06-0171-01A-02 3 0.00000000 0.9674142
## TCGA-06-0173-01A-01 3 0.00000000 0.9674142
## TCGA-06-0179-01A-02 3 0.00000000 0.9674142
## TCGA-06-0182-01A-01 2 0.40297602 0.7033349
## TCGA-06-0185-01A-01 2 0.40297602 0.7033349
## TCGA-06-0195-01B-01 3 0.07072027 0.9549474
## TCGA-06-0208-01B-01 3 0.00000000 0.9674142
## TCGA-06-0214-01A-02 3 0.00000000 0.9674142
## TCGA-06-0219-01A-01 3 0.00000000 0.9674142
## TCGA-06-0221-01A-01 3 0.17667967 0.9214547
## TCGA-06-0237-01A-02 3 0.00000000 0.9674142
## TCGA-06-0240-01A-02 3 0.00000000 0.9674142
## TCGA-08-0349-01A-01 3 0.00000000 0.9674142
## TCGA-08-0380-01A-01 3 0.00000000 0.9674142
## TCGA-08-0386-01A-01 2 0.41337319 0.6829004
## TCGA-08-0520-01A-01 3 0.34722304 0.7457438
## TCGA-02-0007-01A-01 2 0.37390308 0.7481370
## TCGA-02-0009-01A-01 2 0.00000000 0.9574407
## TCGA-02-0016-01A-01 2 0.00000000 0.9574407
## TCGA-02-0021-01A-01 2 0.00000000 0.9574407
## TCGA-02-0023-01B-01 2 0.00000000 0.9574407
## TCGA-02-0027-01A-01 2 0.05107902 0.9468363
## TCGA-02-0038-01A-01 2 0.49588852 0.2733482
## TCGA-02-0043-01A-01 2 0.00000000 0.9574407
## TCGA-02-0070-01A-01 2 0.00000000 0.9574407
## TCGA-02-0102-01A-01 2 0.00000000 0.9574407
## TCGA-02-0260-01A-03 2 0.00000000 0.9574407
## TCGA-02-0269-01B-01 2 0.00000000 0.9574407
## TCGA-02-0285-01A-01 2 0.00000000 0.9574407
## TCGA-02-0289-01A-01 2 0.00000000 0.9574407
## TCGA-02-0290-01A-01 2 0.00000000 0.9574407
## TCGA-02-0317-01A-01 2 0.00000000 0.9574407
## TCGA-02-0333-01A-02 2 0.00000000 0.9574407
## TCGA-02-0422-01A-01 2 0.00000000 0.9574407
## TCGA-02-0430-01A-01 2 0.00000000 0.9574407
## TCGA-06-0125-01A-01 2 0.00000000 0.9574407
## TCGA-06-0126-01A-01 2 0.00000000 0.9574407
## TCGA-06-0137-01A-03 2 0.00000000 0.9574407
## TCGA-06-0145-01A-04 2 0.00000000 0.9574407
## TCGA-06-0148-01A-01 2 0.00000000 0.9574407
## TCGA-06-0187-01A-01 2 0.00000000 0.9574407
## TCGA-06-0211-01B-01 2 0.00000000 0.9574407
## TCGA-06-0402-01A-01 2 0.00000000 0.9574407
## TCGA-08-0246-01A-01 2 0.00000000 0.9574407
## TCGA-08-0354-01A-01 2 0.00000000 0.9574407
## TCGA-08-0355-01A-01 2 0.00000000 0.9574407
## TCGA-08-0357-01A-01 2 0.00000000 0.9574407
## TCGA-08-0358-01A-01 2 0.00000000 0.9574407
## TCGA-08-0375-01A-01 2 0.00000000 0.9574407
## TCGA-08-0511-01A-01 2 0.00000000 0.9574407
## TCGA-08-0514-01A-01 2 0.00000000 0.9574407
## TCGA-08-0518-01A-01 2 0.00000000 0.9574407
## TCGA-08-0529-01A-02 2 0.00000000 0.9574407
## TCGA-08-0531-01A-01 2 0.00000000 0.9574407
## TCGA-02-0057-01A-01 3 0.00000000 0.9674142
## TCGA-02-0004-01A-01 1 0.00000000 0.9861507
## TCGA-02-0006-01B-01 1 0.30905974 0.8390453
## TCGA-02-0025-01A-01 1 0.00000000 0.9861507
## TCGA-02-0033-01A-01 1 0.00000000 0.9861507
## TCGA-02-0034-01A-01 1 0.00000000 0.9861507
## TCGA-02-0039-01A-01 1 0.05107902 0.9784610
## TCGA-02-0051-01A-01 1 0.00000000 0.9861507
## TCGA-02-0054-01A-01 1 0.28325475 0.8619413
## TCGA-02-0055-01A-01 1 0.00000000 0.9861507
## TCGA-02-0059-01A-01 1 0.00000000 0.9861507
## TCGA-02-0064-01A-01 1 0.00000000 0.9861507
## TCGA-02-0075-01A-01 1 0.00000000 0.9861507
## TCGA-02-0079-01A-03 1 0.05107902 0.9784610
## TCGA-02-0085-01A-01 3 0.00000000 0.9674142
## TCGA-02-0086-01A-01 1 0.00000000 0.9861507
## TCGA-02-0099-01A-01 1 0.26468043 0.8762027
## TCGA-02-0106-01A-01 1 0.00000000 0.9861507
## TCGA-02-0107-01A-01 1 0.00000000 0.9861507
## TCGA-02-0111-01A-01 1 0.00000000 0.9861507
## TCGA-02-0326-01A-01 2 0.00000000 0.9574407
## TCGA-02-0337-01A-01 1 0.17667967 0.9365656
## TCGA-06-0122-01A-01 1 0.00000000 0.9861507
## TCGA-06-0124-01A-01 1 0.00000000 0.9861507
## TCGA-06-0130-01A-01 1 0.00000000 0.9861507
## TCGA-06-0139-01A-01 1 0.00000000 0.9861507
## TCGA-06-0143-01A-01 1 0.02888898 0.9825208
## TCGA-06-0147-01A-01 1 0.00000000 0.9861507
## TCGA-06-0149-01A-05 1 0.08869473 0.9690879
## TCGA-06-0152-01A-02 2 0.00000000 0.9574407
## TCGA-06-0154-01A-02 1 0.00000000 0.9861507
## TCGA-06-0164-01A-01 1 0.00000000 0.9861507
## TCGA-06-0175-01A-01 1 0.17667967 0.9365656
## TCGA-06-0176-01A-03 1 0.00000000 0.9861507
## TCGA-06-0184-01A-01 1 0.17667967 0.9365656
## TCGA-06-0189-01A-05 1 0.00000000 0.9861507
## TCGA-06-0190-01A-01 1 0.00000000 0.9861507
## TCGA-06-0194-01A-01 1 0.00000000 0.9861507
## TCGA-06-0197-01A-02 1 0.00000000 0.9861507
## TCGA-06-0210-01A-01 1 0.00000000 0.9861507
## TCGA-06-0397-01A-01 1 0.00000000 0.9861507
## TCGA-06-0409-01A-02 1 0.00000000 0.9861507
## TCGA-06-0412-01A-01 1 0.00000000 0.9861507
## TCGA-06-0644-01A-02 1 0.00000000 0.9861507
## TCGA-06-0645-01A-01 1 0.00000000 0.9861507
## TCGA-08-0346-01A-01 1 0.00000000 0.9861507
## TCGA-08-0352-01A-01 1 0.02888898 0.9825208
## TCGA-08-0360-01A-01 1 0.00000000 0.9861507
## TCGA-08-0390-01A-01 1 0.07072027 0.9739459
## TCGA-08-0392-01A-01 1 0.00000000 0.9861507
## TCGA-08-0509-01A-01 1 0.00000000 0.9861507
## TCGA-08-0510-01A-01 1 0.00000000 0.9861507
## TCGA-08-0512-01A-01 1 0.00000000 0.9861507
## TCGA-08-0522-01A-01 1 0.00000000 0.9861507
## TCGA-12-0619-01A-01 1 0.00000000 0.9861507
## TCGA-12-0620-01A-01 1 0.10542115 0.9593842
MDS or T-sne plots:
dimension_reduction(res, k = 4)
## Error in cmdscale(dist(t(data))): 'k' must be in {1, 2, .. n - 1}
dimension_reduction(res, k = 4, method = "tsne")
## Error in Rtsne.default(X = structure(numeric(0), .Dim = c(0L, 11268L), .Dimnames = list(: Perplexity is too large.
Consistency of classes.
collect_classes(res_list, k = 4)
collect_classes(res)
res = hierarchical_partition(data, top_n = c(1000, 2000, 4000),
known_anno = data.frame(subtype = subtype),
known_col = list(subtype = structure(seq_len(4), names = unique(subtype))))
res = readRDS("~/analysis/TCGA_subgroup_hierarchical_partition.rds")
res
## A 'HierarchicalPartition' object with 'MAD:kmeans' method.
##
## +-- 01, 52 cols
## | |-- 011, 37 cols
## | +-- 010, 15 cols
## +-- 00, 121 cols
## |-- 001, 46 cols
## +-- 000, 75 cols
## |-- 0001, 37 cols
## +-- 0000, 38 cols
## |-- 00001, 16 cols
## +-- 00000, 22 cols
## |-- 000001, 9 cols
## +-- 000000, 13 cols
##
## Following methods can be applied to this 'HierarchicalPartition' object:
## [1] "collect_classes" "get_class" "get_signatures"
## [4] "get_single_run" "show" "test_to_known_factors"
collect_classes(res)
get_class(res)
## TCGA-02-0003-01A-01 TCGA-02-0010-01A-01 TCGA-02-0011-01B-01
## "00001" "000000" "000001"
## TCGA-02-0014-01A-01 TCGA-02-0024-01B-01 TCGA-02-0026-01B-01
## "000000" "000000" "000001"
## TCGA-02-0028-01A-01 TCGA-02-0046-01A-01 TCGA-02-0047-01A-01
## "000000" "00001" "0001"
## TCGA-02-0048-01A-01 TCGA-02-0060-01A-01 TCGA-02-0069-01A-01
## "00001" "0001" "000000"
## TCGA-02-0074-01A-01 TCGA-02-0080-01A-01 TCGA-02-0084-01A-03
## "00001" "000001" "0001"
## TCGA-02-0087-01A-01 TCGA-02-0104-01A-01 TCGA-02-0114-01A-01
## "0001" "000000" "000000"
## TCGA-02-0281-01A-01 TCGA-02-0321-01A-01 TCGA-02-0325-01A-01
## "000000" "001" "000001"
## TCGA-02-0338-01A-01 TCGA-02-0339-01A-01 TCGA-02-0432-01A-02
## "000000" "000000" "000001"
## TCGA-02-0439-01A-01 TCGA-02-0440-01A-01 TCGA-02-0446-01A-01
## "0001" "00001" "0001"
## TCGA-06-0128-01A-01 TCGA-06-0129-01A-01 TCGA-06-0146-01A-01
## "0001" "000001" "000001"
## TCGA-06-0156-01A-01 TCGA-06-0166-01A-01 TCGA-06-0174-01A-01
## "0001" "0001" "00001"
## TCGA-06-0177-01A-01 TCGA-06-0238-01A-02 TCGA-06-0241-01A-02
## "00001" "0001" "00001"
## TCGA-06-0410-01A-01 TCGA-06-0413-01A-01 TCGA-06-0414-01A-01
## "00001" "000000" "00001"
## TCGA-06-0646-01A-01 TCGA-06-0648-01A-01 TCGA-08-0245-01A-01
## "0001" "00001" "00001"
## TCGA-08-0344-01A-01 TCGA-08-0347-01A-01 TCGA-08-0348-01A-01
## "000000" "0001" "00001"
## TCGA-08-0350-01A-01 TCGA-08-0353-01A-01 TCGA-08-0359-01A-01
## "000001" "001" "0001"
## TCGA-08-0385-01A-01 TCGA-08-0517-01A-01 TCGA-08-0524-01A-01
## "000001" "00001" "000000"
## TCGA-12-0616-01A-01 TCGA-12-0618-01A-01 TCGA-02-0089-01A-01
## "00001" "00001" "0001"
## TCGA-02-0113-01A-01 TCGA-02-0115-01A-01 TCGA-02-0451-01A-01
## "001" "0001" "0001"
## TCGA-06-0132-01A-02 TCGA-06-0133-01A-02 TCGA-06-0138-01A-02
## "0001" "0001" "0001"
## TCGA-06-0160-01A-01 TCGA-06-0162-01A-01 TCGA-06-0167-01A-01
## "0001" "0001" "0001"
## TCGA-06-0171-01A-02 TCGA-06-0173-01A-01 TCGA-06-0179-01A-02
## "0001" "0001" "0001"
## TCGA-06-0182-01A-01 TCGA-06-0185-01A-01 TCGA-06-0195-01B-01
## "001" "001" "0001"
## TCGA-06-0208-01B-01 TCGA-06-0214-01A-02 TCGA-06-0219-01A-01
## "0001" "0001" "0001"
## TCGA-06-0221-01A-01 TCGA-06-0237-01A-02 TCGA-06-0240-01A-02
## "0001" "0001" "0001"
## TCGA-08-0349-01A-01 TCGA-08-0380-01A-01 TCGA-08-0386-01A-01
## "0001" "0001" "001"
## TCGA-08-0520-01A-01 TCGA-02-0007-01A-01 TCGA-02-0009-01A-01
## "0001" "001" "001"
## TCGA-02-0016-01A-01 TCGA-02-0021-01A-01 TCGA-02-0023-01B-01
## "001" "001" "001"
## TCGA-02-0027-01A-01 TCGA-02-0038-01A-01 TCGA-02-0043-01A-01
## "001" "001" "001"
## TCGA-02-0070-01A-01 TCGA-02-0102-01A-01 TCGA-02-0260-01A-03
## "001" "001" "001"
## TCGA-02-0269-01B-01 TCGA-02-0285-01A-01 TCGA-02-0289-01A-01
## "001" "001" "001"
## TCGA-02-0290-01A-01 TCGA-02-0317-01A-01 TCGA-02-0333-01A-02
## "001" "001" "001"
## TCGA-02-0422-01A-01 TCGA-02-0430-01A-01 TCGA-06-0125-01A-01
## "001" "001" "001"
## TCGA-06-0126-01A-01 TCGA-06-0137-01A-03 TCGA-06-0145-01A-04
## "001" "001" "001"
## TCGA-06-0148-01A-01 TCGA-06-0187-01A-01 TCGA-06-0211-01B-01
## "001" "001" "001"
## TCGA-06-0402-01A-01 TCGA-08-0246-01A-01 TCGA-08-0354-01A-01
## "001" "001" "001"
## TCGA-08-0355-01A-01 TCGA-08-0357-01A-01 TCGA-08-0358-01A-01
## "001" "001" "001"
## TCGA-08-0375-01A-01 TCGA-08-0511-01A-01 TCGA-08-0514-01A-01
## "001" "001" "001"
## TCGA-08-0518-01A-01 TCGA-08-0529-01A-02 TCGA-08-0531-01A-01
## "001" "001" "001"
## TCGA-02-0057-01A-01 TCGA-02-0004-01A-01 TCGA-02-0006-01B-01
## "0001" "010" "011"
## TCGA-02-0025-01A-01 TCGA-02-0033-01A-01 TCGA-02-0034-01A-01
## "010" "010" "010"
## TCGA-02-0039-01A-01 TCGA-02-0051-01A-01 TCGA-02-0054-01A-01
## "011" "010" "011"
## TCGA-02-0055-01A-01 TCGA-02-0059-01A-01 TCGA-02-0064-01A-01
## "010" "010" "011"
## TCGA-02-0075-01A-01 TCGA-02-0079-01A-03 TCGA-02-0085-01A-01
## "011" "011" "0001"
## TCGA-02-0086-01A-01 TCGA-02-0099-01A-01 TCGA-02-0106-01A-01
## "011" "011" "010"
## TCGA-02-0107-01A-01 TCGA-02-0111-01A-01 TCGA-02-0326-01A-01
## "011" "011" "001"
## TCGA-02-0337-01A-01 TCGA-06-0122-01A-01 TCGA-06-0124-01A-01
## "011" "011" "011"
## TCGA-06-0130-01A-01 TCGA-06-0139-01A-01 TCGA-06-0143-01A-01
## "010" "010" "011"
## TCGA-06-0147-01A-01 TCGA-06-0149-01A-05 TCGA-06-0152-01A-02
## "011" "011" "001"
## TCGA-06-0154-01A-02 TCGA-06-0164-01A-01 TCGA-06-0175-01A-01
## "011" "011" "011"
## TCGA-06-0176-01A-03 TCGA-06-0184-01A-01 TCGA-06-0189-01A-05
## "010" "011" "010"
## TCGA-06-0190-01A-01 TCGA-06-0194-01A-01 TCGA-06-0197-01A-02
## "011" "011" "011"
## TCGA-06-0210-01A-01 TCGA-06-0397-01A-01 TCGA-06-0409-01A-02
## "011" "011" "011"
## TCGA-06-0412-01A-01 TCGA-06-0644-01A-02 TCGA-06-0645-01A-01
## "011" "010" "011"
## TCGA-08-0346-01A-01 TCGA-08-0352-01A-01 TCGA-08-0360-01A-01
## "011" "011" "011"
## TCGA-08-0390-01A-01 TCGA-08-0392-01A-01 TCGA-08-0509-01A-01
## "011" "010" "011"
## TCGA-08-0510-01A-01 TCGA-08-0512-01A-01 TCGA-08-0522-01A-01
## "011" "011" "010"
## TCGA-12-0619-01A-01 TCGA-12-0620-01A-01
## "011" "011"
collect_classes(res, depth = 4)
sig = get_signatures(res, depth = 4)
## get signatures at node 000 with 2 subgroups.
## get signatures at node 00 with 3 subgroups.
## get signatures at node 01 with 2 subgroups.
## get signatures at node 01 with 2 subgroups.
venn_euler(sig)
